DSI Spring Symposium 2019

SUNday, March 31st

10:30 am - 5 pm

RION BallRoom @ REITz union


Come spend your Saturday at the largest DSI event of the year - our annual Symposium. 

Begin the day with coffee, remarks from DSI leadership and the UFII Director, and a keynote.

The symposium continues with speakers from a wide range of research fields at UF in three breakout sessions of four speakers each.

Learn about computer vision, bioinformatics, political forecasting, business analytics, and more.

Our symposium will also include two rounds of workshops with several choices in each round- so you can brush up on your Python, learn about data visualization, or deepen your knowledge of machine learning.

This is a fantastic opportunity to network with students and faculty who are passionate about the impact of data science and the tools they utilize to realize that impact. 

Coffee and Lunch will be served. 

If you plan to attend, please RSVP through THIS FORM 

While we urge you to RSVP for food estimates, we will not turn anyone away, so feel free to bring a friend! 

The schedule is below: 

Registration & Coffee in Grand Ballroom
Vinay Chitepu- What is DSI?
Dr. George Michailidis - What is the UFII?
Key Note Speaker
Networking Lunch
Breakout Session 1 (20 minute presentations, 10 minute Q&A)
Breakout Session 2 (20 minute presentations, 10 minute Q&A)
Breakout Session 3 (20 minute presentations, 10 minute Q&A)
Workshop Session 1 (4 workshops)
Workshop Session 2 (4 workshops)
Closing Remarks and How to Get Involved


10:30 - 11:00
11:00 - 11:15
11:15 - 11:30
11:30 - 12:00
12:00 - 1:20
1:30 - 2:00
2:10 - 2:40
2:50 - 3:20
3:30 - 4:10
4:20 - 5:00
5:05 - 5:10


Opening Remarks and Introduction to DSI
Vinay Chitepu, DSI President

Keynote Speaker - TBD


Introduction to UFII: The UF Informatics Institute
Dr. George Michailidis, UFII Director and Professor of Statistics

Dr. Michailidis is the Professor and Director of the Informatics Institute. He has made very important contributions to multivariate data analysis as well as modeling, analysis and control of networks. His current research interests include multivariate analysis and machine learning, computational statistics, change-point estimation, stochastic processing networks, bioinformatics, network tomography, visual analytics, statistical methodology with applications to computer, communications and sensor networks.

Breakout Sessions 1, 2 & 3: 1:30 - 3:20 pm

Check back later for more info!


Workshop Session 1: 3:30 - 4:10 pm,
(4 workshops)

For all workshops, see instructions below

Salon A - The Tools of Data Science

New to Data Science? This workshop is for you! We cover what tools/software you’ll need to get started with our workshops and data science on your own. Step by step instructions on downloading necessary software and files.

Salon D - Natural Language Processing with Python
Instructor: Allison Kahn, DSI Secretary

This workshop covers introductory techniques and resources for NLP and ends with the implementation of a Named Entity Recognition algorithm. No advanced coding experience required!

Salon E - Data Visualization
Instructor: Delaney Gomen, DSI Internal Vice President

This workshop, you will learn to use the Python data visualization library Seaborn to create stunning visuals inside of Python!

Salon H - Python 2
Instructor: Meghana Tatineni, DSI Workshop Coordinator Lead

This workshop is an introduction to machine learning in Python and will cover machine learning techniques such as support vector machine (SVM), random forest classifier, and the scikit-learn machine learning Python library.

Workshop Session 2: 4:20 - 5:00 pm,
(4 workshops)

For all workshops, see instructions below

Salon A - Introduction to Python
Instructor: Aarti Tolani, DSI Workshop Coordinator

This workshop is an introduction to Python and will cover all the basics of Python to get you started with using one of the most popular languages for data science. No programming experience needed.

Salon D - Web Scraping
Instructor: Allison Kahn, DSI Secretary

Web Scraping is a very useful method used by data scientists to gather data from websites. This workshop will introduce the basics of web scraping and review common web scraping methodologies. Although there are many different ways to scrape data from websites we will cover some of the most popularly used libraries that python has to offer.

Salon E - Statistics for Data Scientists
Instructor: Delaney Gomen, DSI Internal Vice President

Statistics for Data Scientists is an intro to the most commonly used and useful statistical concepts, implemented in python. This workshop is perfect for students who want to turn theoretical statistical concepts into a practical toolkit for Data Science problems, and will cover basics of concepts like the Central Limit Theorem, common distributions, and Causal Inference.

Salon H - Neural Networks
Instructor: Meghana Tatineni, DSI Workshop Coordinator Lead

Neural networks are some of the most powerful machine learning algorithms available today, with applications in computer vision, speech recognition, pattern classification, and many more.

Pre-Workshop Instructions

For all workshops, follow this link, (https://github.com/dsiufl/SpringSymposium2018), click the green “Clone or Download” button, and select “Download ZIP”.  The folder you download will contain important files that are used for all workshops.

Introduction to Python, Data Visualization in Python using Seaborn, Introduction to Natural Language Processing in Python, and Machine Learning in Python:
Using this link, (https://www.continuum.io/downloads) download and install Anaconda Python distribution for Python 2.
Click “clone or download" in the top right-hand corner, and select "download zip."  Use this link:  https://github.com/dsiufl/SpringSymposium2018. Open up the Anaconda Navigator, select “Jupyter Notebook”, and the notebook will launch in a web browser.  Through this page, you can navigate through files on your computer.  Navigate to the files you downloaded from GitHub, and select through the Jupyter webpage, you will be able to run the iPython notebook.  

Amazon AWS Tutorial:
Follow the instructions at http://amzn.to/2GuijZ3 at least 24 hours before the workshop.